Abut, Tayfun;
Salkım, Enver;
Demosthenous, Andreas;
(2025)
Performance Improvement in a Vehicle Suspension System with FLQG and LQG Control Methods.
Actuators
, 14
(3)
, Article 137. 10.3390/act14030137.
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Abstract
This study investigates the effect of active control on a quarter-vehicle suspension system. The car suspension system was modeled using the Lagrange–Euler method. The linear quadratic Gaussian (LQG) and fuzzy linear quadratic Gaussian (FLQG) control methods were designed and used for active control to increase vehicle handling and passenger comfort, with the aim of reducing or eliminating vibrations by performing active control of passive suspension systems using these methods. The optimum values of the coefficients of the points where the membership functions of the LQG and Fuzzy LQG methods touch were obtained using the grey wolf optimization (GWO) algorithm. The success of the control performance rate of the applied methods was compared based on the passive suspension system. In addition, the obtained results were compared with each other and with other studies using the integral time-weighted absolute error (ITAE) performance criterion. The proposed control method yielded significant improvements in vehicle parameters compared with the passive suspension system. Vehicle body movement, vehicle acceleration, suspension deflection, and tire deflection improved by approximately 88.2%, 91.5%, 88%, and 89.4%, respectively. Thus, vehicle driving comfort was significantly enhanced based on the proposed system.
| Type: | Article |
|---|---|
| Title: | Performance Improvement in a Vehicle Suspension System with FLQG and LQG Control Methods |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/act14030137 |
| Publisher version: | https://doi.org/10.3390/act14030137 |
| Language: | English |
| Additional information: | Copyright © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Active control; linear quadratic Gaussian (LQG); fuzzy linear quadratic Gaussian (FLQG); grey wolf optimization (GWO) algorithm |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10206291 |
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